Mining Individual Performance Indicators in Collaborative Development Using Software Repositories

A better understanding of the individual developers¿ performance has been shown to result in benefits such as improved project estimation accuracy and enhanced software quality assurance. However, new challenges of distinguishing the individual activities involved in software evolution arise when considering collaborative development environments. Since software repositories such as version control systems (VCS) and bug tracking systems (BTS) are available for most software projects and hold a detailed and rich record of the historical development information, this paper presents our experiences mining individual performance indicators in collaborative development environments by using these repositories. The base of our key idea is to identify the complexity metrics (in the code base) and field defects (from bug tracking system) at individual-level by incorporating the historical data from version control system. We also remotely measure and analyze these indicators mined from a libre project jEdit, which involves around one hundred developer. The results show that these indicators are feasible and instructive in the understanding of the individual performance.